The Problems You'll Solve

At Carta, our employees set out on a mission to unlock the power of equity ownership for more people in more places. We believe that the problems we solve today unlock the opportunities of tomorrow.

As a Senior Machine Learning Engineer at Carta, you'll spend a third of your time partnering with domain experts across the company to analyze and explore Carta's proprietary document repository and data set. Another third will be dedicated to building machine learning models to power new products, automate complex document workflows, and accelerate Carta's business. The remaining third will involve developing Carta's machine learning infrastructure. Example responsibilities will include:

• Perform exploratory analyses to understand the dynamics of private markets and ownership from source-of-record documents and systems.
• Develop LLM-powered pipelines to classify complex legal documents and extract key information from these docs to automate onboarding to our suite of products.
• Develop machine learning models to power new financial products and to extract trends from performance of existing products.
• Build and deploy containerized prediction services and integrate them with our data pipelines.
• Partner with product managers, engineers, designers, and business teams to incorporate ML-generated estimates and benchmarks into products and user-flows.
• Own, coordinate, and solve complex, cross-functional problems that extend beyond the traditional boundaries of machine learning.

The Team You'll Work With

At Carta, our Machine Learning team is on a mission to power data products and automation through cutting-edge techniques. We work closely with Carta's core business units and product teams to develop estimation-based data products and large language model (LLM)-powered document intelligence capabilities. This role is foundational to our team, where you'll work with one of the world's most valuable datasets and document repositories. Our models directly enable revenue growth and operational efficiency for the company.

Our team consists of specialized Machine Learning scientists and engineers, collaborating with product analytics and data engineering experts. We foster a culture of partnership, working closely with teams across Carta to solve impactful problems. We strongly believe that being helpful accelerates results, and we support one another to achieve success at Carta.

The Impact You'll Have

You will own significant projects that directly align with the company's strategic initiatives in document intelligence, data products, and data quality. Your contributions will empower leaders across the organization to deliver innovative products, optimize operational efficiency, and make well-informed product decisions. Additionally, you will have the opportunity to develop foundational infrastructure for our team and establish best practices for integrating our machine learning models into production environments. Your work will not only impact Carta's current machine learning capabilities but also pave the way for future engineers, enabling them to build upon your efforts seamlessly.

About You

Candidates must have a strong foundation in statistics and machine learning, be proficient in SQL and Python, and have an analytical mindset. You have a strong bias towards simplicity, are excited by “zero to one” projects, and can efficiently communicate findings to leadership. Example traits that we value:

• 5+ years of industry experience solving complex data problems with descriptive and predictive statistical models
• Proficiency with modern programming languages (Python, R, SQL, etc.) and datastores (Redshift or similar)
• A deep understanding of modern statistical and machine learning models, when to apply them, and how to evaluate their performance
• Experience with large language models (LLMs) and their applications in document intelligence, information extraction, and text classification tasks.
• Strong written and verbal communication skills, with a particular emphasis on data visualization
• A collaborative attitude and a helpful personality

• Experience with containerizing ML models and integrating them into production workflows
• Experience with building simple ETL pipelines (Airflow or similar) to schedule model training / predictions